학술논문

A Robust SIFT Descriptor for Multispectral Images
Document Type
Periodical
Source
IEEE Signal Processing Letters IEEE Signal Process. Lett. Signal Processing Letters, IEEE. 21(4):400-403 Apr, 2014
Subject
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Signal processing algorithms
Histograms
Robustness
Equations
Indexes
Visualization
Materials
Harris Laplace interest regions
image matching
multispectral images and SIFT
Language
ISSN
1070-9908
1558-2361
Abstract
This letter presents a novel method for the description of multispectral image keypoints. The method proposed is based on a modified SIFT algorithm. It uses normalized gradients as local image features for the description of keypoints in order to achieve robustness against non linear intensity changes between multispectral images. The experimental results show that the method proposed achieves a better matching performance and outperforms the SIFT algorithm.